{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# 语义分割和数据集\n",
    "\n",
    "最重要的语义分割数据集之一是[Pascal VOC2012](http://host.robots.ox.ac.uk/pascal/VOC/voc2012/)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "origin_pos": 4,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import os\n",
    "import torch\n",
    "import torchvision\n",
    "from d2l import torch as d2l\n",
    "\n",
    "d2l.DATA_HUB['voc2012'] = (d2l.DATA_URL + 'VOCtrainval_11-May-2012.tar',\n",
    "                           '4e443f8a2eca6b1dac8a6c57641b67dd40621a49')\n",
    "\n",
    "voc_dir = d2l.download_extract('voc2012', 'VOCdevkit/VOC2012')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "将所有输入的图像和标签读入内存"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "origin_pos": 7,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [],
   "source": [
    "def read_voc_images(voc_dir, is_train=True):\n",
    "    \"\"\"读取所有VOC图像并标注。\"\"\"\n",
    "    txt_fname = os.path.join(voc_dir, 'ImageSets', 'Segmentation',\n",
    "                             'train.txt' if is_train else 'val.txt')\n",
    "    mode = torchvision.io.image.ImageReadMode.RGB\n",
    "    with open(txt_fname, 'r') as f:\n",
    "        images = f.read().split()\n",
    "    features, labels = [], []\n",
    "    for i, fname in enumerate(images):\n",
    "        features.append(torchvision.io.read_image(os.path.join(\n",
    "            voc_dir, 'JPEGImages', f'{fname}.jpg')))\n",
    "        labels.append(torchvision.io.read_image(os.path.join(\n",
    "            voc_dir, 'SegmentationClass' ,f'{fname}.png'), mode))\n",
    "    return features, labels\n",
    "\n",
    "train_features, train_labels = read_voc_images(voc_dir, True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "绘制前5个输入图像及其标签"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "origin_pos": 10,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 540x216 with 10 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "n = 5\n",
    "imgs = train_features[0:n] + train_labels[0:n]\n",
    "imgs = [img.permute(1,2,0) for img in imgs]\n",
    "d2l.show_images(imgs, 2, n);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "列举RGB颜色值和类名"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "origin_pos": 12,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [],
   "source": [
    "VOC_COLORMAP = [[0, 0, 0], [128, 0, 0], [0, 128, 0], [128, 128, 0],\n",
    "                [0, 0, 128], [128, 0, 128], [0, 128, 128], [128, 128, 128],\n",
    "                [64, 0, 0], [192, 0, 0], [64, 128, 0], [192, 128, 0],\n",
    "                [64, 0, 128], [192, 0, 128], [64, 128, 128], [192, 128, 128],\n",
    "                [0, 64, 0], [128, 64, 0], [0, 192, 0], [128, 192, 0],\n",
    "                [0, 64, 128]]\n",
    "\n",
    "VOC_CLASSES = ['background', 'aeroplane', 'bicycle', 'bird', 'boat',\n",
    "               'bottle', 'bus', 'car', 'cat', 'chair', 'cow',\n",
    "               'diningtable', 'dog', 'horse', 'motorbike', 'person',\n",
    "               'potted plant', 'sheep', 'sofa', 'train', 'tv/monitor']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "查找标签中每个像素的类索引"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "origin_pos": 15,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [],
   "source": [
    "def voc_colormap2label():\n",
    "    \"\"\"构建从RGB到VOC类别索引的映射。\"\"\"\n",
    "    colormap2label = torch.zeros(256 ** 3, dtype=torch.long)\n",
    "    for i, colormap in enumerate(VOC_COLORMAP):\n",
    "        colormap2label[\n",
    "            (colormap[0] * 256 + colormap[1]) * 256 + colormap[2]] = i\n",
    "    return colormap2label\n",
    "\n",
    "def voc_label_indices(colormap, colormap2label):\n",
    "    \"\"\"将VOC标签中的RGB值映射到它们的类别索引。\"\"\"\n",
    "    colormap = colormap.permute(1, 2, 0).numpy().astype('int32')\n",
    "    idx = ((colormap[:, :, 0] * 256 + colormap[:, :, 1]) * 256\n",
    "           + colormap[:, :, 2])\n",
    "    return colormap2label[idx]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "例如"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "origin_pos": 17,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(tensor([[0, 0, 0, 0, 0, 0, 0, 0, 0, 1],\n",
       "         [0, 0, 0, 0, 0, 0, 0, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 0, 0, 1, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 0, 1, 1, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 0, 1, 1, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 1, 1, 1, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 0, 1, 1, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 0, 1, 1, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 0, 0, 1, 1, 1, 1],\n",
       "         [0, 0, 0, 0, 0, 0, 0, 0, 1, 1]]),\n",
       " 'aeroplane')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y = voc_label_indices(train_labels[0], voc_colormap2label())\n",
    "y[105:115, 130:140], VOC_CLASSES[1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "使用图像增广中的随机裁剪，裁剪输入图像和标签的相同区域"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "origin_pos": 22,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 540x216 with 10 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def voc_rand_crop(feature, label, height, width):\n",
    "    \"\"\"随机裁剪特征和标签图像。\"\"\"\n",
    "    rect = torchvision.transforms.RandomCrop.get_params(\n",
    "        feature, (height, width))\n",
    "    feature = torchvision.transforms.functional.crop(feature, *rect)\n",
    "    label = torchvision.transforms.functional.crop(label, *rect)\n",
    "    return feature, label\n",
    "\n",
    "imgs = []\n",
    "for _ in range(n):\n",
    "    imgs += voc_rand_crop(train_features[0], train_labels[0], 200, 300)\n",
    "\n",
    "imgs = [img.permute(1, 2, 0) for img in imgs]\n",
    "d2l.show_images(imgs[::2] + imgs[1::2], 2, n);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "自定义语义分割数据集类"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "origin_pos": 25,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [],
   "source": [
    "class VOCSegDataset(torch.utils.data.Dataset):\n",
    "    \"\"\"一个用于加载VOC数据集的自定义数据集。\"\"\"\n",
    "\n",
    "    def __init__(self, is_train, crop_size, voc_dir):\n",
    "        self.transform = torchvision.transforms.Normalize(\n",
    "            mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])\n",
    "        self.crop_size = crop_size\n",
    "        features, labels = read_voc_images(voc_dir, is_train=is_train)\n",
    "        self.features = [self.normalize_image(feature)\n",
    "                         for feature in self.filter(features)]\n",
    "        self.labels = self.filter(labels)\n",
    "        self.colormap2label = voc_colormap2label()\n",
    "        print('read ' + str(len(self.features)) + ' examples')\n",
    "\n",
    "    def normalize_image(self, img):\n",
    "        return self.transform(img.float())\n",
    "\n",
    "    def filter(self, imgs):\n",
    "        return [img for img in imgs if (\n",
    "            img.shape[1] >= self.crop_size[0] and\n",
    "            img.shape[2] >= self.crop_size[1])]\n",
    "\n",
    "    def __getitem__(self, idx):\n",
    "        feature, label = voc_rand_crop(self.features[idx], self.labels[idx],\n",
    "                                       *self.crop_size)\n",
    "        return (feature, voc_label_indices(label, self.colormap2label))\n",
    "\n",
    "    def __len__(self):\n",
    "        return len(self.features)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "读取数据集"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "origin_pos": 27,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "read 1114 examples\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "read 1078 examples\n"
     ]
    }
   ],
   "source": [
    "crop_size = (320, 480)\n",
    "voc_train = VOCSegDataset(True, crop_size, voc_dir)\n",
    "voc_test = VOCSegDataset(False, crop_size, voc_dir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "origin_pos": 30,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([64, 3, 320, 480])\n",
      "torch.Size([64, 320, 480])\n"
     ]
    }
   ],
   "source": [
    "batch_size = 64\n",
    "train_iter = torch.utils.data.DataLoader(voc_train, batch_size, shuffle=True,\n",
    "                                    drop_last=True,\n",
    "                                    num_workers=d2l.get_dataloader_workers())\n",
    "for X, Y in train_iter:\n",
    "    print(X.shape)\n",
    "    print(Y.shape)\n",
    "    break"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "整合所有组件"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "origin_pos": 33,
    "tab": [
     "pytorch"
    ]
   },
   "outputs": [],
   "source": [
    "def load_data_voc(batch_size, crop_size):\n",
    "    \"\"\"加载VOC语义分割数据集。\"\"\"\n",
    "    voc_dir = d2l.download_extract('voc2012', os.path.join(\n",
    "        'VOCdevkit', 'VOC2012'))\n",
    "    num_workers = d2l.get_dataloader_workers()\n",
    "    train_iter = torch.utils.data.DataLoader(\n",
    "        VOCSegDataset(True, crop_size, voc_dir), batch_size,\n",
    "        shuffle=True, drop_last=True, num_workers=num_workers)\n",
    "    test_iter = torch.utils.data.DataLoader(\n",
    "        VOCSegDataset(False, crop_size, voc_dir), batch_size,\n",
    "        drop_last=True, num_workers=num_workers)\n",
    "    return train_iter, test_iter"
   ]
  }
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